Simulating Observations of Southern Ocean Clouds and Implications for Climate
Simulating Observations of Southern Ocean Clouds and Implications for Climate
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DOI：
10.1029/2020jd032619
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发表时间：
2020-11-16
影响因子：
4.4
通讯作者：
Wu, W.
中科院分区：
文献类型：
--
作者：
Gettelman, A.;Bardeen, C. G.;Wu, W.
南大洋（S。海洋云对气候预测很重要。然而，以前的全球气候模式未能准确地代表云相分布在这个观测稀疏的地区。在这项研究中，从南大洋云，辐射，气溶胶，运输实验研究（SOCRATES）实验的数据进行了比较，从全球气候模式（社区大气模式，CAM）的约束模拟。微推版本的CAM被发现重现许多详细的原位观测，如云的位置，云相，边界层结构的功能。CAM6中的模拟改进了S.调整了允许更多过冷液体的冰成核和云微物理方案的海洋云。模拟和观测的水凝物粒径分布之间的比较表明，模拟的水凝物粒径分布代表双峰的形状和形式的观测分布，这是显着的模型和观测之间的尺度差异。由于模型假设与反演假设不匹配，因此很难将云物理学与卫星观测进行比较。该模型对S.海洋云和气溶胶仍然存在，但详细的云物理参数化提供了一个基础，过程水平的改进和直接比较的观测。这是至关重要的，因为云反馈和气候敏感性对S的代表性很敏感。海洋云。
Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds.